Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-10T19:01:13.243Z Has data issue: false hasContentIssue false
  • English
  • Français

Cluster Molecular Dynamics on Massively Parallel Computers

Published online by Cambridge University Press:  26 February 2011

K. M. Nelson ,
S. T. Smith  and
L. T. Wille
K. M. Nelson
Affiliation:
Department of Physics, Florida Atlantic University, Boca Raton, FL 33431
S. T. Smith
Affiliation:
Department of Physics, Florida Atlantic University, Boca Raton, FL 33431
L. T. Wille
Affiliation:
Department of Physics, Florida Atlantic University, Boca Raton, FL 33431
Get access

Abstract

We report the results of computer simulations of phase transitions in noble-gas clusters. The calculations were performed on a MasPar MP-l massively parallel computer with 8,192 processing elements (PE's). We discuss the efficient implementation of molecular dynamics algorithms for small clusters on this type of architecture. The simulations are based on a classical Lennard-Jones pair potential and follow the temporal evolution of the system by numerically integrating Newton's equations of motion using the Gear algorithm. Because the number of particles is much smaller than the number of PE's, optimal partitioning of the processing element array is an essential and non-trivial task.

Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 278: Symposium W – Computational Methods in Materials Science , 1992 , 231
Copyright
Copyright © Materials Research Society 1992

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Knight, W. D. and Cohen, M. L., Phys. Today 43, 42 (1990).Google Scholar
2. Halicioglu, T. and Bauschlicher, C. W. Jr., Rep. Prog. Phys. 51, 883 (1988).Google Scholar
3. Berry, R. S., Beck, T. L., Davis, H. L., and Jellinek, J., Adv. Chem. Phys. 70, 75 (1988).Google Scholar
4. Bowler, K. C. and Pawley, G. S., Proc. IEEE 72, 42 (1984).Google Scholar
5. Greenwell, D. L., Kalia, R. K., Patterson, J. C., and Vashishta, P. D., in Scientific Applications of the Connection Machine, edited by Simon, H. D. (World Scientific, Singapore, 1989), p. 252; Int. J. High Speed Comp. 1, 321 (1989).Google Scholar
6. Petersen, H. G. and Perram, J. W., Mol. Phys. 67, 849 (1989).Google Scholar
7. Boyer, L. L. and Pawley, G. S., J. Comp. Phys. 78, 405 (1988).Google Scholar
8. Maresca, M. and Fountain, T. J. (eds.), Proc. IEEE 79, 1991 (special issue).Google Scholar
9. Blank, T., Proceedings IEEE Compcon Spring 1990, IEEE (1990), 20–24; Nickolls, J.R., 25-28.Google Scholar
10. Hockney, R. W. and Eastwood, J. W., Computer Simulation Using Particles (McGraw-Hill, New York, 1981).Google Scholar
11. Hoover, W. G., Molecular Dynamics (Springer-Verlag, Berlin, 1986).Google Scholar
12. Allen, M. P. and Tildesley, D. J., Computer Simulation of Liquids (Clarendon Press, Oxford, 1987).Google Scholar
13. Lustig, S., Cristy, J., and Pensak, D., these Proceedings.Google Scholar
14. Hoare, M. R. and Pal, P., Adv. Phys. 20, 161 (1971); 24, 645 (1975).Google Scholar
15. Press, W. H., Flannery, B. P., Teukolsky, S. A., and Vetterling, W. T., Numerical Recipes, Cambridge University Press, Cambridge (1986).Google Scholar
16. Car, R. and Parrinello, M., Phys. Rev. Lett. 55, 2471(1985); for an application to small clusters see: P. Ballone, W. Andreoni, R. Car, and M. Parrinello, Phys. Rev. Lett. 60, 271 (1988).Google Scholar